code: def count_parameters(model):
      return sum(
          [
              np.prod(p.size())
              for p in model.parameters()
              if p.requires_grad
          ]
      )
  
file_path: dgl/examples/pytorch/grace/main.py
imports: import argparse
  import warnings
  import numpy
  import torch
  import torch.nn
  from aug import aug
  from dataset import load
  from eval import label_classification
  from model import Grace
label_desc: Use image node_id 1 for calling a global function with example usage: count_parameters(model) and returns: sum